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--- |
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library_name: transformers |
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license: gemma |
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base_model: google/gemma-2-9b |
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tags: |
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- alignment-handbook |
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- trl |
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- sft |
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- generated_from_trainer |
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- trl |
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- sft |
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- generated_from_trainer |
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datasets: |
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- oxford-llms/ultrachat_filtered |
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- oxford-llms/Magpie-Qwen2.5-Pro-1M-v0.1-filtered |
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- oxford-llms/european_social_survey_2020_sft |
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- oxford-llms/european_social_survey_2023_sft |
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- oxford-llms/world_values_survey_2017_2022_sft |
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model-index: |
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- name: ox-llms-9b-gemma-sft |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# ox-llms-9b-gemma-sft |
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This model is a fine-tuned version of [google/gemma-2-9b](https://huggingface.co/google/gemma-2-9b) on the oxford-llms/ultrachat_filtered, the oxford-llms/Magpie-Qwen2.5-Pro-1M-v0.1-filtered, the oxford-llms/european_social_survey_2020_sft, the oxford-llms/european_social_survey_2023_sft and the oxford-llms/world_values_survey_2017_2022_sft datasets. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8087 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- total_train_batch_size: 16 |
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- total_eval_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 0.7037 | 1.0 | 7750 | 0.8465 | |
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| 0.5064 | 2.0 | 15500 | 0.8087 | |
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### Framework versions |
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- Transformers 4.45.1 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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